Bloomsbury Publishing Plc Paperback English
Leveraging Artificial Intelligence to Transform Teacher Education Accreditation
A Framework for Innovation and Equity
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This book explores how emerging technologies are reshaping the landscape of higher education quality assurance. Focused on educator preparation programs (EPPs), this timely volume examines how AI tools can transform data-driven decision-making, streamline accreditation processes, and promote institutional equity and accountability. Written by accreditation experts, the book moves beyond technical explanations to address the human dimensions of AI—ethics, fairness, transparency, and professional judgment. Through real-world examples and research-based insights, it offers practical guidance for integrating AI responsibly into accreditation systems while maintaining the integrity of educational evaluation. From automated data analysis to predictive modeling and ethical oversight, the book highlights both the opportunities and risks of AI-driven transformation. Grounded in current scholarship and informed by decades of accreditation practice, this work invites faculty, administrators, and policymakers to imagine a future where innovation and human judgment coexist to advance continuous improvement, educational quality, and professional integrity.
This book explores how emerging technologies are reshaping the landscape of higher education quality assurance. Focused on educator preparation programs (EPPs), this timely volume examines how AI tools can transform data-driven decision-making, streamline accreditation processes, and promote institutional equity and accountability. Written by accreditation experts, the book moves beyond technical explanations to address the human dimensions of AI—ethics, fairness, transparency, and professional judgment. Through real-world examples and research-based insights, it offers practical guidance for integrating AI responsibly into accreditation systems while maintaining the integrity of educational evaluation. From automated data analysis to predictive modeling and ethical oversight, the book highlights both the opportunities and risks of AI-driven transformation. Grounded in current scholarship and informed by decades of accreditation practice, this work invites faculty, administrators, and policymakers to imagine a future where innovation and human judgment coexist to advance continuous improvement, educational quality, and professional integrity.